Book Image

Neural Networks with R

By : Balaji Venkateswaran, Giuseppe Ciaburro
Book Image

Neural Networks with R

By: Balaji Venkateswaran, Giuseppe Ciaburro

Overview of this book

Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve wide range of problems in different areas of AI and machine learning. This book explains the niche aspects of neural networking and provides you with foundation to get started with advanced topics. The book begins with neural network design using the neural net package, then you’ll build a solid foundation knowledge of how a neural network learns from data, and the principles behind it. This book covers various types of neural network including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but will also explore generalization of these networks. Later we will delve into combining different neural network models and work with the real-world use cases. By the end of this book, you will learn to implement neural network models in your applications with the help of practical examples in the book.
Table of Contents (14 chapters)
Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

R for DNNs


In the previous section, we clarified some key concepts that are at the deep learning base. We also understood the features that make the use of deep learning particularly convenient. Moreover, its rapid diffusion is also due to the great availability of a wide range of frameworks and libraries for various programming languages.

The R programming language is widely used by scientists and programmers, thanks to its extreme ease of use. Additionally, there is an extensive collection of libraries that allow professional data visualization and analysis with the most popular algorithms. The rapid diffusion of deep learning algorithms has led to the creation of an ever-increasing number of packages available for deep learning, even in R.

The following table shows the various packages/interfaces available for deep learning using R:

CRAN package

Supported taxonomy of neural network

Underlying language/vendor

MXNet

Feed-forward, CNN

C/C++/CUDA

darch

RBM, DBN

C/C++

deepnet

Feed-forward, RBM, DBN, autoencoders...